Artificial Intelligence thread

iewgnem

Captain
Registered Member
care to summarize? - "US closed source models are still the best, but Chinese open source models are good enough that no one will pay up?"
More like, closed source models are not actually better in any meaningful sense and people and companies can become extremely rational when it comes to spending money.
 

iewgnem

Captain
Registered Member
Gemini 3 Pro and even its Deep Think version already feel nerfed just weeks later.... Google is watering down, and its no where close to the perf/power/intelligence of the benchmarks...

What Deepseek isnt admitting to is that with Kimi K2 Thinking, Z-Image, Qwen models and its own V3.2, all open-weights and open license, it establishes a permanent cognitive floor... that will hit white collar knowledge workers in the US the hardest while making the US AI tech companies ability to extract AI API tax from the rest of the world, including US itself, much harder...

OpenAI, Anthropihic, will never turn a profit. AGI is no where in site, LLMs rate are plateuing, and US AI companies are not advancing fast enough to outrun its cash spend vs gpu obselence vs Chinese open weights pressure

High HA EUV is end of road, China will soon catch up with SMEE/SMIC/Huawei...

LLMs /Transformers will never get us to full AGI...

In the beginning of 2025 folks were hoping China might eventually come out with a reasoning model on par with o1 by end of year... I think we are well past that now.

We have seen how fragile US really is if China presses hard on REE cards...

Deepseek is being disingenious on level of Gordan Chang here, its the West that is running out of time, a dollar short and day late... earlier this year I was legit worried it waa going to be the other way around...

China has already won
I find the fact that DS still calls their SOTA models V3 hilarious.
 

iewgnem

Captain
Registered Member
DeepSeek says that closed source models are accelerating at a faster rate than open sourced models. Thus, the gap instead of narrowing, is actually widening

Keep in mind this is written as the intro to their SOTA model, which they still calls V3.
You usually outline the problem that your paper solves in the intro.

I also find it funny that Chinese open source models are so good people just automatically assume what's released must be their latest and there were no delay from completion to release. Unlike closed source models they're not making money on it so there's nothing to be lost by holding back and releasing it at the optimal time for street cred, especially if you're also a hedge fund....
 

Eventine

Senior Member
Registered Member
More like, closed source models are not actually better in any meaningful sense and people and companies can become extremely rational when it comes to spending money.
Closed source models from top labs are still meaningfully better. If you've tried them side by side, you'd know this. I've actually sat and rated many generations from e.g. Nano Banana 2 vs. Qwen Edit, and yes Nano Banana 2 remains superior (mainly due to its multi-modal understanding capabilities and presumably much larger knowledge base, which is reflected in its model size). But the issue is that Nano Banana 2 is 1) expensive, 2) highly censored, and 3) not customizable in any way, since it's a proprietary API service. This makes it much less attractive to build around compared to Chinese models.

The race is still on and even though I'm optimistic, I can see why Deep Seek would claim that closed models are accelerating their rate of improvement. Infinite money and scale does have some benefits in enabling thousands of parallel experiments, top tier AI talent (many poached from China), and data gathering / labeling / collection at a rate that start-ups like Deep Seek, Z.AI, and Moon Shot would find hard to match. It's why Western labs still have the lead in frontier performance, but the industry is learning that often times, you don't need frontier performance and it isn't necessarily worth the cost, either.
 

iewgnem

Captain
Registered Member
Closed source models from top labs are still meaningfully better. If you've tried them side by side, you'd know this. I've actually sat and rated many generations from e.g. Nano Banana 2 vs. Qwen Edit, and yes Nano Banana 2 remains superior (mainly due to its multi-modal understanding capabilities and presumably much larger knowledge base, which is reflected in its model size). But the issue is that Nano Banana 2 is 1) expensive, 2) highly censored, and 3) not customizable in any way, since it's a proprietary API service. This makes it much less attractive to build around compared to Chinese models.

The race is still on and even though I'm optimistic, I can see why Deep Seek would claim that closed models are accelerating their rate of improvement. Infinite money and scale does have some benefits in enabling thousands of parallel experiments, top tier AI talent (many poached from China), and data gathering / labeling / collection at a rate that start-ups like Deep Seek, Z.AI, and Moon Shot would find hard to match. It's why Western labs still have the lead in frontier performance, but the industry is learning that often times, you don't need frontier performance and it isn't necessarily worth the cost, either.
I do compare them side by side between work and personal and no they're not meaningfully better for what I do.
And that's when I don't have to pay for the former.
Or perhaps because I don't pay for the former I don't have a reason to convince myself it's better by telling myself it has presumably larger knowledge base.
 
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